Submitted 9 March 2015Accepted 29 July 2015Published 18 August 2015

Corresponding authorMark John Costello,m.costello@auckland.ac.nz

Academic editorMagnus Johnson

Additional Information andDeclarations can be found onpage 21

DOI 10.7717/peerj.1201

Copyright2015 Costello et al.

Distributed underCreative Commons CC-BY 4.0

OPEN ACCESS

Biological and ecological traits of marinespeciesMark John Costello1, Simon Claus2, Stefanie Dekeyzer2,Leen Vandepitte2, Eamonn O Tuama3, Dan Lear4 andHarvey Tyler-Walters4

1 Institute of Marine Science, University of Auckland, New Zealand2 Vlaams Instituut voor de Zee, VLIZ–InnovOcean site, Oostende, Belgium3 Global Biodiversity Information Facility, Copenhagen, Denmark4 Marine Biological Association, Plymouth, Devon, UK

ABSTRACTThis paper reviews the utility and availability of biological and ecological traits formarine species so as to prioritise the development of a world database on marinespecies traits. In addition, the ‘status’ of species for conservation, that is, whetherthey are introduced or invasive, of fishery or aquaculture interest, harmful, or usedas an ecological indicator, were reviewed because these attributes are of particularinterest to society. Whereas traits are an enduring characteristic of a species and/orpopulation, a species status may vary geographically and over time. Criteria forselecting traits were that they could be applied to most taxa, were easily available,and their inclusion would result in new research and/or management applications.Numerical traits were favoured over categorical. Habitat was excluded as it can bederived from a selection of these traits. Ten traits were prioritized for inclusion inthe most comprehensive open access database on marine species (World Register ofMarine Species), namely taxonomic classification, environment, geography, depth,substratum, mobility, skeleton, diet, body size and reproduction. These traits andstatuses are being added to the database and new use cases may further subdivide andexpand upon them.

Subjects Aquaculture, Fisheries and Fish Science, Biodiversity, Ecology, Marine Biology,TaxonomyKeywords Taxonomy, Distribution, Feeding, Diet, Body-size, Life-history, Habitat, Environment,Databases, Depth

INTRODUCTIONWorld databases of marine species have now been published but are limited to taxonomic

(e.g., WoRMS) and distribution (e.g., Ocean Biogeographic Information System, OBIS)

data (Costello et al., 2007). The benefits of these databases could be multiplied by

associating species with richer ecological and biological information. Classification of

species provides hypotheses for the evolution, organisation, and ecological interactions of

biodiversity from genes to ecosystems. Initially, newly discovered species are classified by

their taxonomic relationships, which are intended to indicate their evolutionary lineages

and origins. New research challenges this classification, resulting in changes to species

genera and even changes in higher taxonomic classification (Costello et al., 2013). Species

How to cite this article Costello et al. (2015), Biological and ecological traits of marine species. PeerJ 3:e1201; DOI 10.7717/peerj.1201

are readily classified by their geography, for example what region, country or locality they

occur in, and within that, by environment (e.g., freshwater, terrestrial, marine, soils or

sediments). Ecological classification is more complex, and may refer to their habitat, a

concept combining the physical environment and associated species with which the species

typically occurs (Costello, 2009). Species may be associated with a guild of co-occurring

species similar in distribution and habit; such as benthos, plankton, sessile epifauna, or

ectoparasites. Biological classification includes attributes of life stages, reproduction, body

size, behaviour, feeding method, and diet. However, data on such attributes or species

traits are widely scattered in the literature and are time consuming to gather (Naeem &

Bunker, 2009; Tyler et al., 2012). To solve this, databases of traits for (a) 21,000 species of

freshwater plants, invertebrates and fish in Europe (Schmidt-Kloiber & Hering, 2015), and

(b) terrestrial plants (Naeem & Bunker, 2009; Kattge et al., 2011), have been established.

A rich terminology surrounds descriptions of a species biology and ecology, with

sometimes different definitions for the same terms, synonymous terms, and context

dependent (e.g., habitat) terms (e.g., Lepczyk, Lortie & Anderson, 2008). This terminology

has developed over several hundred years of natural history, in different languages, and

often terms have multiple meanings in common use. For example, “littoral” habitat can be

the marine zone between the low and high tide marks, extend to the continental shelf and

include coastal river catchments, and refer to the edge of freshwater lakes (Aquatic Sciences

and Fisheries Abstracts, 2014). The lack of standard use of terms can compromise the

bringing together of this knowledge from different sources, and thus limit understanding

of patterns beyond local scale, context specific studies (Lepczyk, Lortie & Anderson, 2008).

Hence the publication of a glossary particular to the marine biology community (Costello

et al., 2010) that followed a popular biology and ecology dictionary (Lincoln, Boxshall &

Clark, 1998). That glossary provided the starting point for a standard vocabulary to be used

in the World Register of Marine Species (WoRMS) database (Costello et al., 2013).

In this paper, we review and classify traits so as to decide which should be prioritised

to apply to marine species in WoRMS. In parallel, we are developing a wider vocabulary

and classification of traits that would provide the basis for expanding the traits in WoRMS

in the longer-term. Thus, scientists interested in more detailed trait classifications for a

particular taxon or ecological function could build on the more general primary traits

proposed here.

Biodiversity databasesGlobal databases that integrate information on species force the development of standard

classifications (Costello & Vanden Berghe, 2006). This process then enables analyses across

many species and datasets previously compromised by inconsistent terminologies. The

World Register of Marine Species (WoRMS) is such a database (Costello et al., 2013;

Boxshall et al., 2014). It contains the names of almost all known marine species and

classifies them (1) taxonomically, (2) by environment (e.g., marine, freshwater, terrestrial),

and (3) by geographic distribution. Each additional field in the database may have a

multiplier effect on how useful the database may be to researchers, educators and other

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 2/29

users. For example, the availability of the author and year of description of each species,

and their synonyms, has facilitated research into the rate of discovery of marine species

(Costello & Wilson, 2011; Mora et al., 2011; Appeltans et al., 2012; Costello, Wilson &

Houlding, 2012; Costello, Wilson & Houlding, 2013a; Costello, May & Stork, 2013b; Costello,

May & Stork, 2013c; Costello, Houlding & Wilson, 2014a; Costello, Houlding & Joppa, 2014b;

Costello, Vanhoorne & Appeltans, 2015).

Several databases already include information on marine species traits, namely WoRMS,

BIOTIC (Marshall et al., 2006), FishBase (Froese & Pauly, 2014), and SeaLifeBase. The

SeaLifeBase data fields are a subset of those in FishBase. These databases have already

applied some traits to marine species and it can be preferable to build on these applications

than start anew. However, they contain hundreds of traits which would take considerable

effort and resources to apply to all marine species. Thus, in this paper we present a rationale

for the prioritisation of traits for immediate inclusion in WoRMS.

User needsParticular groups of users have begun to develop thematic databases within WoRMS. For

example, species involved in Harmful micro-Algal Blooms (HAB) (Moestrup et al., 2013),

occurring in the deep sea (WoRDSS, Glover, Higgs & Horton, 2013), and that have been

introduced by human activities (Pagad et al., 2015). Biological traits may also be used to

help predict a species sensitivity to toxic substances (Baird & Van den Brink, 2007), but may

be a poor predictor of its likelihood of going extinct, becoming invasive, and/or its reaction

to climate change (Angert et al., 2011). However, a failure to detect which traits affect a

species’ ecology at a global level may be because traits are operational within a local and

regional context (Vermeij & Leighton, 2009). That is, the importance of traits is relative to

the ecological and environmental factors acting on individuals of a species at any time.

Traits that determine ecological function can be better predictors of invasiveness of

marine fouling communities (e.g., Atalah, Costello & Anderson, 2007; Atalah et al., 2007;

Wahl et al., 2011) and be less sensitive to sampling effort for sediment macrobenthos

(Tornroos & Bonsdorff, 2012) than taxonomic richness. The richness of traits in an

assemblage of species is positively correlated with species richness but not necessarily

linearly (e.g., Cumming & Child, 2009; Tornroos & Bonsdorff, 2012). Other users of marine

species data include ecologists studying the functional role of species in ecosystems (e.g.,

Naeem & Bunker, 2009; Bostrom, Tornroos & Bonsdorff, 2010). They may wish to know a

species’ place in the food web and body size. The value of biodiversity to society is being

quantified in terms of ecosystem goods and services, with the species’ importance being

dependent on their functional role in the ecosystems. Conservation biologists conduct

species extinction risk assessments using standard criteria based on species biological (e.g.,

population size and trends, generation time, age at maturity, longevity, fecundity, natural

mortality) and geographic (e.g., range size) traits IUCN, 2012; Grave et al., 2015). Invasive

species are an increasing concern. So information on which species have been introduced

beyond their native range by human activities and have become invasive is in demand

(Blackburn et al., 2014; Jeschke et al., 2014). Whether a species is likely to be transported

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 3/29

by human activities, such as in ballast water, fouling on a ship-hull or aquaculture

equipment, may depend on its habitat, habit and modes of dispersal (Brine, Hunt &

Costello, 2013). Gallien, Carboni & Munkemuller (2014) proposed phenotypic similarity,

based on taxonomic and functional traits, can predict invasiveness in communities.

We propose that the traits that users need should be prioritised for inclusion in

databases. Ideally, this should result in users publishing new analyses resulting from

the inclusion of traits in the database, which in turn would drive improvements in the

quality and quantity of trait information. For the purpose of this paper, we identify two

main classes of users, scientists (usually ecologists) and wider society. Ecologists require

traits that identify a species’ role in an ecosystem. These traits provide the basis for

understanding and assessment of species socio-economic importance. Society is interested

in species by virtue of their importance as food (e.g., fisheries, aquaculture), threat to

human and animal health (e.g., toxic algae and other species, sharks), pests (e.g., invasive),

and likelihood of extinction.

It must also be recognised that most traits are not available in the literature for most

species. For British North Sea macrobenthos, body size was the most available trait (Webb,

Tyler & Somerfield, 2009). Tyler et al. (2012) found there was no trait data available for

about a quarter of the North Sea macrobenthic species, and most traits were only available

for about another quarter. They found that adult mobility, feeding method, development

mode, sociability, migration and life span were available for only 30–40% of the species

with body size data. The most valuable traits for end users wishing to compare traits across

taxa will be those available for most species.

DataData related to species may be of numerical, continuous and categorical form (Tornroos

& Bonsdorff, 2012). Most traits are categorical, that is they are a concept described in a

word that may or may not apply to a species, such as whether a species is a parasite or

not. Tornroos & Bonsdorff (2012) show the utility of categorical traits for marine benthos

because a wider variety of concepts and traits can be applied to species than if limited to

numerical measures. However, some traits can be described by numerical data, such as

body size and depth distribution, and geographic distributions by continuous variables

such as contours on maps. Numerical and continuous trait data are preferable because they

can be converted into categorical (concept-based) data but not the reverse. Thus, an actual

depth range would be preferred to ‘bathyal’ or ‘mesopelagic’ because the latter categories

cannot be converted to a depth range.

Most traits will need to be applied to a particular life stage, probably the adult stage in

the first instance. In some cases traits may vary between sexes and populations (e.g., body

size). Population level traits would require each trait to be placed in the context of

the sampled location, and it may be unclear as to how representative they may be of

the species.

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 4/29

AimsIn this paper, we review traits assigned to marine species in existing biodiversity databases,

and evaluate which would be most useful to users to prioritise for inclusion in WoRMS.

The criteria for prioritisation were that (1) the trait could (in theory) be applied across

most taxa, (2) that information on the trait existed for most taxa, and (3) it was likely that

the availability of the trait would result in new uses of the databases in the short-term. As

there are arguments for more and fewer traits depending on user needs, we created a top-10

shortlist. If a trait could be applied at a higher taxon level (e.g., family, order, phylum) this

would make it easier to apply across many species. Where possible, we favoured numerical

and continuous traits over categorical. Thus, although traits peculiar to populations rather

than a species, and secondary traits derived from others, were not prioritized for inclusion

in WoRMS, these are included in a wider classification and vocabulary for discussion by

users.

METHODSThe prioritization of traits for marine species involved a review of the use of traits in liter-

ature and related databases, and asking experts in a range of taxa (including crustaceans,

molluscs, fish, echinoderms, algae, birds, nematodes, annelids), and benthic and pelagic

ecology of coastal and deep sea environments (listed in the Acknowledgements) their

opinion on how to rank traits by importance and what uses they may make of an enhanced

marine species trait database. Initial capture of potential traits and trait values made use

of spreadsheets but as the development of a traits vocabulary is, of necessity, a community

process involving discussion and feedback leading to consensus, the suitability of the open

source Semantic MediaWiki (SMW) (https://semantic-mediawiki.org/) was investigated

for building a hierarchical list of traits. SMW, an extension to MediaWiki, the wiki engine

underlying Wikipedia, allows the content within wiki pages to be semantically marked

up for subsequent processing and querying. It is well suited for capturing hierarchical

knowledge organisation systems such as thesauri or other taxonomies. SMW is receiving

some attention within biodiversity informatics having been adopted by Biowikifarm (http:

//biowikifarm.net/) which hosts several installations, e.g., for the TDWG draft standard,

Audubon Core (http://terms.tdwg.org/wiki/Audubon Core), with a dedication to long

term sustainability through a consortium providing service sponsorship. SMW provides a

number of advantages. Each term (i.e., concept or trait) can have its own web page where

labels, definitions and examples can be presented. User friendly web forms can be used

in place of raw wiki mark-up by domain experts to add content including translations to

multiple languages. An associated discussion page allows capture of comments relating to a

term so they are all conveniently available for review and building consensus. Relationships

between terms can be established and the terms can be grouped into categories and

collections. SMW can be scripted to output collections of terms in standard formats such

as Resource Description Framework (RDF) (http://www.w3.org/standards/techs/rdf)

and Simple Knowledge Organization System (SKOS) (http://www.w3.org/TR/skos-

reference/) thereby making them more easily usable by other applications. Following best

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 5/29

practices, SMW supports the issuing of resolvable identifiers for terms and the importing

of already existing terms from other vocabularies so they can be re-used rather than

re-invented.

For the marine species traits vocabulary, a customised version of SMW was established

within the VLIZ hosted Coastal Wiki (http://www.coastalwiki.org). This wiki is an

encyclopaedia providing up-to-date high quality information for coastal and marine

professionals, which is continuously improved, complemented and updated by expert

users. The wiki was implemented to allow collaborative writing by authors who can add

new terms or improve and update existing articles. The main difference between this wiki

and the online Wikipedia are the procedures to maintain the quality, consistency and

comprehensiveness of the information (Claus et al., 2008). Within the wiki, an additional

namespace, ‘traits’ was created. The namespace name is a variable for searching in, and

reporting on, sets of pages. It is also used to apply features that configure the sets of pages

in one namespace differently from another namespace. So every trait name, value, concept

and collection falls under the namespace ‘traits’ within the Coastal and Marine Wiki, and is

available under the same base URL as the World Register of Marine Species at http://www.

marinespecies.org/traits/wiki. It is intended that the wiki will provide further functionality

based on user feedback. Developing a hierarchy of traits, expressed formally in SKOS, will

provide the foundation for future, semantically richer ontologies where a marine species

traits ontology can draw on other published vocabularies and ontologies, including the

Environment Ontology (http://environmentontology.org) and the Phenotypic Quality

Ontology (PATO) (wiki.obofoundry.org/wiki/index.php/PATO).

RESULTSTraits in databasesMost of the traits in BIOTIC (Table 1) and FishBase (Table 2) can be applied to most

marine species. The trait categories and descriptors used in BIOTIC were developed by the

MarLIN project, with minor amendments (Hiscock, Jackson & Lear, 1999; Tyler-Walters et

al., 2001). They encompass distribution, biology, phenotypic and genetic attributes, and

importance to humans. FishBase has evolved over 20 years and is the most comprehensive

database on any global taxon. However, in both databases there can be overlap between

groups of traits, and some traits developed for particular use cases or projects at a level

of detail would be impractical to achieve for most marine species in the short-term.

For example, BIOTIC has separate classifications for habit, sociability, environmental

position, growth form, mobility, dependency and host, which contain overlapping

and/or strongly inter-dependent traits, and include bioturbation and fragility traits that

are applicable to limited groups of species. Thus, it is necessary to review and select a

simpler classification of traits in the first instance. Other classes of traits in BIOTIC include

‘Reproduction’ (regeneration, frequency, development mechanism, reproductive type),

and ‘Distribution and Habitat.’ The latter includes: Migration Pattern, Biological Zone

(depth zone categories), Physiographic features, Salinity, Substratum (includes biogenic

habitats, crevices and sediment mixtures), Water Flow Rate, and Wave Exposure. In

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 6/29

Table 1 Benthic invertebrate traits in BIOTIC. List of benthic invertebrate traits compiled in the biological traits information catalogue BIOTIC(Marshall et al., 2006). Where more than one category of traits applies, all relevant categories are recorded.

Subject area Traits (categories)

Biology Growth form—44 categories e.g., Algal gravel, Bivalved, Foliose, Turbinate, Encrusting

Growth rate (expressed as µm, mm, cm per day/month/year)

Size (max.)—6 categories from Very small (<1 cm) to Large (>50 cm)

Environmental position—14 categories e.g., Epibenthic, Infaunal, Interstitial, Pelagic, Demersal

Habit—10 categories e.g., Attached, Bed forming, Burrow dwelling, Erect Encrusting

Height (above substratum)—(mm/cm/m)

Flexibility—High (>45◦)/Low (10–45◦)/None (<10◦)

Fragility—Fragile, Intermediary, Robust

Mobility/movement—Swimmer, Crawler, Burrower, Drifter, Attached (permanent, temporary)

Dispersal potential (adult)—7 categories from None, Very limited (<1 m) to >10 km

Feeding method—19 categories e.g., Autotroph, Detritivore, Grazer, Predator

Typical food type (descriptive text)

Bioturbator—4 categories e.g., Diffusive mixing, Conveyor belt transport

Sociability—Free living, Gregarious, Colonial

Dependency—Independent, Parasitic, Mutualist, Inquilinist, Commensal, Host

Toxicity—(Yes/No)

Host (for another species)—(Yes/No)

Habitat Distribution (UK & Global)—(descriptive text)

Biogeographic range—(descriptive text)

Migratory—Resident, Passive, Active (Diel, Seasonal)

Depth range (expressed as metres below chart datum)

Substratum preferences—38 categories, e.g., Bedrock, Boulders, Mud, Gravel, Mixed, Other

Physiography—9 categories e.g., Open coast, Strait/sound, Sea loch, Ria/Voe, Estuary

Biological zone—Benthic (15 categories), Pelagic (8 categories)

Wave exposure—8 categories form Extremely Exposed, to Ultra Sheltered

Tidal strength—Very Strong, Strong, Moderately Strong, Weak, Very Weak (negligible)

Salinity (range)—Full (30–40 psu), Variable (18-40 psu), Reduced (18–30 psu), Low (<18 psu)

Life-history Reproductive type—17 categories e.g., Budding, Fission, Gonochoristic, Hermaphrodite

Regeneration potential—yes/no

Reproductive frequency—7 categories e.g., Semelparous, Annual episodic, Biannual protracted

Reproductive season—(range of months or seasons)

Reproductive location—As adult, Adult burrow, Brooding, Sediment surface, Water column

Life-span (max.)—8 categories from <1 year, to 100+ years

Generation time 8 categories from <1 year, to 100+ years

Age at maturity—8 categories from <1 year, to 100+ years

Fecundity—number of eggs

Egg or propagule size—value (µm, mm, cm)

Fertilization type—External, Internal, Self-fertile, None (asexual)

Developmental mechanism—10 categories e.g., Planktotrophic, Oviparous, Viviparous

Larval Larva dispersal potential—7 categories from None, Very limited (<1 m) >10 km

Larval settlement period—(range of months or seasons)

Duration of larval stage—<1 day, 1 day, 2–10 days, 11–30 days, 1–2 months, 1–6 months, >6 months

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 7/29

Table 2 Traits in FishBase. A summary of traits included in FishBase (Froese & Pauly, 2014).

Taxonomy Biology Status

Common names Age Mass conversion Introductions

Synonyms Size Metabolism Aquaculture

Growth Diseases Aquaculture profile

Distribution Length–weight relationship Fish sounds Processing

Countries Length–length Gill area

FAO areas Length–frequencies Otoliths Genetics

Ecosystems Morphometrics Brains Strains

Occurrences Morphology Vision Allele frequencies

Maturity Swimming speed Heritability

Ecology Spawning Swimming type

Diet Fecundity Ecotoxicology Stocks

Food items Eggs Ciguatera Recruitment

Food consumption Egg development Abundance

Ration Larvae

Predators Larval dynamics

Reproduction

BIOTIC, body size data was available for ca 96% of the 685 species covered, but only

half of the traits were complete for 60% of the species (Table 3).

Taxon-specialist databases tend to contain traits that are difficult to apply to other

taxa. For example, the TRY plant-trait database focuses on 52 groups of 681 traits

characterizing the vegetative and regeneration stages of the plant life cycle, including

growth, reproduction, dispersal, establishment and persistence (Kattge et al., 2011). These

groups of traits were collectively agreed to be the most relevant for plant life history

strategies, vegetation modelling and global change responses on the basis of existing

shortlists and consultation with vegetation modellers and plant ecologists. Traits were

summarized in groups, e.g., the group ‘leaf nitrogen content’ consists of the three traits:

leaf nitrogen content per dry mass, leaf nitrogen content per area and nitrogen content per

leaf. In the case of respiration, the database contained 105 related traits: different organs,

different reference values (e.g., dry mass, area, volume, nitrogen) and the temperature

dependence of respiration (e.g., Q10). Specific information for each trait is available on

the TRY website (http://www.try-db.org). Previously, Cornelissen et al. (2003) proposed

30 functional “soft traits” for flowering plants for tackling large-scale ecological questions.

These were grouped into vegetative (e.g., growth form, height, life span, phenology),

regenerative (e.g., dispersal, seed size), leaf (e.g., size, nitrogen content), stem (e.g., density)

and root (e.g., length, diameter, depth) traits. A study on bryophyte moss communities

used metrics of plant size (i.e., shoot density, mass, height, surface area to volume ratio)

(Michel et al., 2012). Traits common to all these databases were measures of growth form or

habit, body size, longevity, nutrition, and dispersal mechanism.

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Table 3 Completeness of traits in BIOTIC. The completeness of trait information for species in BIOTIC(Marshall et al., 2006).

Trait No. species Percentage of species (n = 685)

Body-size 664 96.93

Mobility 407 59.42

Sociability 395 57.66

Feeding method 392 57.23

Habit 369 53.87

Fragility 366 53.43

Flexibility 363 52.99

Developmental mechanism 340 49.64

Regeneration 330 48.18

Reproductive type 322 47.01

Dependency 315 45.99

Growth form 302 44.09

Substratum 296 43.21

Food type 288 42.04

Distribution in UK 283 41.31

Depth range 283 41.31

Global distribution 282 41.17

Environmental position 282 41.17

Life-span 276 40.29

Reproductive season 272 39.71

Fertilization type 258 37.66

Reproductive frequency 254 37.08

Reproductive location 247 36.06

Maturity 236 34.45

Migratory 232 33.87

Larval settling time 230 33.58

Biological zone 221 32.26

Dispersal potential (Adult) 215 31.39

Salinity 212 30.95

Physiography 206 30.07

Dispersal potential (Larvae) 166 24.23

Wave exposure 166 24.23

Bioturbator 158 23.07

Egg size 158 23.07

Fecundity 155 22.63

Larval settlement period 148 21.61

Tidal strength 138 20.15

Generation time 136 19.85

Growth rate 115 16.79

Height 96 14.01

Biogeography 93 13.58

Toxic 50 7.30

Host 6 0.88

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 9/29

PRIORITISING TRAITSDistribution: environment, geography, depth, habitat, ecosystem,seascapeThe term distribution may be applied to the environment and habitat in which a species

lives, and its spatial distribution by geography, depth, and time. Temporal distribution is a

numerical measure applied to particular traits, such as life span, duration of a life stage or

time periods when a species changes its spatial distribution (e.g., population movement or

migration). Thus, we do not propose it as a separate trait here because it can be included as

a metric of traits.

EnvironmentIn WoRMS, most species have already been attributed to one of the following environ-

ments: marine, brackish, freshwater, terrestrial, and combinations thereof (Table 4). When

species are recognised as a host or parasite of one or more species they are then classified

according to the environment of their host. A host may be considered the ‘habitat’ of a

commensal species, including parasites and mutually beneficial symbiotic relationships

(e.g., anemone fish). Many species change their habitat during different life stages, such as

from planktonic larvae to benthic adults or parasites. Thus, a core attribute of a life stage

is whether it is living in the pelagic or benthic environment. Pelagic may be sub-divided

into pleuston, neuston, plankton (drifting), nekton, phyto-, zooplankton, demersal (=

hyperbenthos, benthopelagic).

The occurrence of species in the fossil record has also been implemented in WoRMS.

The indication of the fossil status of a taxon—Recent or Fossil or both Recent &

Fossil—was found to be a necessity, as the type species of genera can contain extant taxa,

extant species can be attributed to fossil species in taxonomic history and documenting

fossil taxa can help prevent the accidental creation of junior homonyms. As the indication

Recent and/or Fossil is too coarse for research questions involving evolution, phylogeny,

biodiversity or biogeography, WoRMS is now also including detailed stratigraphic data.

As WoRMS follows international standards on the level of taxonomy, it was decided

to also follow the international standards for stratigraphy, by making use of the latest

version of the hierarchically structured International Stratigraphic Chart (Cohen et al.,

2013). Each stratigraphic range added to WoRMS is tied to a source, allowing traceability

of information. As the hierarchy of the International Stratigraphic Chart is included,

information can be added on the level available in the literature, and extrapolations can

be made through the WoRMS search interface: e.g., all taxa appearing in a certain Age will

automatically be included when searching for the corresponding Era or Epoch.

GeographyWoRMS utilises a gazetteer that enables species to be attributed to any predefined

geographic area, including seas, oceans, and countries available at www.marineregions.

org (Claus et al., 2014). Additional regions have also been identified for fisheries

management and conservation reporting but are not presently included in WoRMS.

Cross-mapping of geographic areas is possible to some extent. OBIS and the Global

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 10/29

Table 4 Proposed priority traits for WoRMS. The 10 proposed priority traits and how they would be applied to adult marine species.

Trait Relevance Categories Numerical

1. Taxonomic Related species have similar traits so taxonomicrelationships predict traits of related species

Kingdom to genus Not applicable

2. Environment Most studies are confined to a particularenvironment so this trait allows users to quicklyisolate species of interest for their purpose.

Marine, brackish, freshwater,terrestrial, pelagic, benthic

Not applicable

3. Geography Distribution is the most sought after informationon species after its taxonomy.

Locality name Latitude-longitude coordinates(in OBIS)

4. Depth The most widely available variable to distinguishspecies’ habitat.

Intertidal, subtidal (epipelagic)deep-sea (>500 m)

Deepest and shallowest depthrecorded in (1) literature and(2) in OBIS, above and belowChart datum (±m).

5. Body-size Related to position in food web, species abundance,metabolic rates, and dispersal.

– Maximum body length in mmexcluding appendages. Maximumtotal body weight of individual.

6. Substratum A key physical factor determining species habitat. Sediment, hard, biological Not applicable

7. Mobility Indicates the dispersal potential of the life-stage. Mobile, immobile (sessile) Potential metres in life-time

8. Skeleton Calcareous important for oceanacidification and fossil record.Gelatinous important due to sampling difficulties,role as predators, and hazard to humans.

Calcareous (aragonite, calcite),chitinous, silicious, exoskeleton,endoskeleton, plant cell wall

Not applicable

9. Diet Influence on abundance of other species,determines position in food web.

Carnivore, herbivore, parasite,detrivore, phototrophic,chemoautotrophic

Isotopic signatureTrophic level

10. Reproduction May relate to the ability of a population to recoverfrom reduced abundance or invisibility.

Sexual, asexual

Biodiversity Information Facility (GBIF) provide actual latitude and longitude coordinates

for over half of all marine species, often with place names and an indicator of geographic

accuracy (e.g., 1 km2) (Costello & Wieczorek, 2014). They enable mapping of these

locations as points, and from these geographic distribution can be inferred. Thus, through

both the georeferenced place names in WoRMS and point locations in OBIS and GBIF,

there are established methods to map marine species geographic distribution. Where

distribution is not available as latitude–longitude coordinates, we recommend using the

most geographically precise locality name possible; for example, ‘Dublin Bay’ should not

be reported as the Irish Sea or north-east Atlantic.

DepthThere are several terms used to describe depth zones in the literature, although not with

a consistently defined depth range (reviewed by Costello, 2009). Terms like neritic and

oceanic, epipelagic, abyssal, and bathyal are concepts rather than strict depth zones.

For example, the epipelagic is the zone with enough light for photosynthesis, and light

penetration will vary with water clarity. Thus, photosynthesis occurs at greater depths

in offshore waters than in more turbid coastal waters. If a species would have its deepest

and shallowest known records reported, it could then be placed within any depth zone

classification. The WoRMS deep sea database (Glover, Higgs & Horton, 2013) has chosen

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 11/29

500 m as the boundary for the ‘deep sea’ because below that temperature and light

generally show little variation (Rex, 1981). A minimal depth zone classification could thus

distinguish intertidal (or littoral, i.e., seabed exposed at low tide), subtidal (or sublittoral)

and deep sea (>500 m depth) zones (Table 4). Beyond that it would be preferable to assign

actual depth ranges from known data (e.g., from OBIS and literature).

HabitatHabitat is highly context dependent and sometimes loosely applied. The term can

sometimes be incorrectly used for a locality where a species occurs, or a seascape (e.g.,

bay, lough, estuary, island) which can contain a combination of habitats (Costello, 2009).

However, in ecology a habitat is the physical environment in which a species lives at least

part of its life. Many species change habitat during different life stages, such as from

planktonic larvae to benthic adults or vice-versa. Habitats need to be distinguished from

ecosystems and seascapes. The latter are defined by environment and geomorphology, and

may contain any combination of benthic and pelagic habitats. They are now best mapped

by remote sensing methods (e.g., acoustic, airborne, satellite) (Andrefouet et al., 2008;

Costello, 2009).

A standard habitat and biotope classification was developed for European seas by the

BioMar-LIFE project (Connor et al., 2004; Costello & Emblow, 2005) and subsequently ex-

panded as part of the European Union Nature Information System (EUNIS) classification

(Galparsoro et al., 2012). This is now well-established as part of the regulatory framework

for nature conservation in Europe and its basic units of depth zonation, benthic substrata

and wave and current exposure are common to other classifications. Its most detailed level

describes a biotope, namely the physical habitat and associated community of species. A

species may occur in more than one biotope. Some species define a biotope or habitat by

virtue of providing a biogenic habitat within which other species live, such as reefs formed

by corals, bivalves and worms, and beds of seaweed or seagrass. Thus, some species live in

biological (biogenic) habitats, including symbionts and parasites. Matching each species to

a biotope is possible where such ecological data are available. However, a simpler approach

to characterise a habitat would be to record a species depth distribution, and if benthic, the

substratum, or if biological, the host.

The simplest classification of benthic substrata would be sediment [i.e., mud (including

silt), sand, gravel (including pebbles and cobbles), boulders] and hard substrata (e.g.,

bedrock, artificial substrata)(Table 4). As with environment, a species may occur in

several of these (e.g., mud and sand, boulders and bedrock). A biological habitat could

be subdivided into commensal, parasitic, and symbiotic. Thus the combination of depth,

substratum and/or biological habitat (e.g., host if a parasite or symbiont, if associated with

biological habitat), could be used to assign species to the habitat classification. A species’

abundance is likely to vary between habitats, and be facultative or obligate, such that

it may occur in several which may make defining its habitat difficult. We recommend

only assigning species to any habitat it is frequently found in. The small number of

species limited to reduced or variable salinity (brackish and estuarine) habitats can be

distinguished using the ‘environment’ classification. Thus we do not propose a separate

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 12/29

trait called ‘habitat’ but rather users can derive it as appropriate to their needs using

combinations of environment, depth and substratum (Table 4).

EcosystemThe literature can often refer to species as being associated with habitats or geographic

areas dominated or characterised by particular species, such as coral reef, seagrass or

kelp ecosystems. Ecosystems are geographic areas defined by biologically significant

environmental boundaries. Thus, they contain a diversity of habitats, and not the same

proportion or combination of habitats in different areas. Because species are associated

with habitats they are indirectly associated with ecosystems. Thus, it is difficult to assign

an ‘ecosystem’ to a species. However, a species’ environmental limits can be defined and

its geographic distribution can be mapped. Similarly, environmentally defined ecosystems

may occur in different parts of the world but with different species. Thus, associating

species with ecosystems is outside the scope of a species based classification. Rather,

habitats could be mapped to ecosystems.

SeascapeSeascapes, sometimes called landscapes, geomorphological, topographic and physio-

graphic features, are sometimes confused with habitats (Costello, 2009). However, while

species are clearly associated with habitats, seascapes contain an idiosyncratic combination

of habitats. Thus, like the situation with ecosystems, it is not necessary to assign species

to seascapes because a coastal species, for example, may be associated with all potential

seascapes depending on the habitats they contain. Thus, we consider seascapes outside the

scope of a species classification. They may be applied when mapping habitats in particular

geographic regions.

BiologicalLife stageThe traits of most marine species vary significantly between life stages. Most fish,

crustaceans and molluscs have planktonic larvae but some cnidarians have pelagic adult

stages. Thus, it is essential to qualify a trait by the life stage to which it applies. For some

taxa, such as peracaridean crustaceans which brood their eggs and lack free living larvae,

the traits may be the same for adults and juveniles. Thus, we propose four basic life stages:

adult (mature), juvenile (immature but morphologically adult), larva (morphologically

different from adult form), and egg (or propagule, spore). Some taxa have specific

nomenclature for different life stages and multiple larval forms (e.g., nauplius, zoea,

megalopa, phyllosoma, veliger) but these cannot be applied across all species. At present,

we propose to prioritise traits for the adult life stage only because this is generally more

available, can be applied to more species, and would be users’ first expectation.

Body sizeBody size is perhaps the most fundamental trait as it correlates with other traits, for

example, enabling conversion of length and abundance to biomass (e.g., Gifford & Caron,

2000; Postel, Fock & Hagen, 2000). In a review of 22 research areas using traits, body size

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was the most commonly used (Naeem & Bunker, 2009). It is also the most widely available

trait (Table 3; Webb, Tyler & Somerfield, 2009; Tyler et al., 2012). Field sampling typically

selects species based on body size, whether large enough to be identifiable on sight in the

field, or if captured through nets (plankton) or sieves (benthos) of particular mesh size.

Larger animal species tend to be top predators and smaller tend to be herbivores and/or

detrivores, so body size correlates with food web structure, trophic levels, and energy flow

in ecosystem (Gerlach, Hahn & Schrage, 1985). Some studies found peaks and troughs in

body size distributions of benthic fauna (e.g., Gerlach, Hahn & Schrage, 1985). However,

other studies did not, instead finding that size-distribution patterns reflected the species

present rather than any habitat influenced structure (Dolbeth, Raffaelli & Pardal, 2014).

Pelagic species have long been classified by body size because it is conveniently related to

sampling method and can simplify data presentation and analysis (Platt & Denman, 1977).

Nine classes of body length, each increasing by a factor of ten from 0.02 µm virio-plankton

to 20 m nekton, are commonly used but this does not imply any ecological meaning to the

size classes (Sieburth, Smetacek & Lenz, 1978). That said, viruses are all in the <0.2 µm size

class; most bacteria in the 0.02–2.0 µm; most fungi, phytoplankton and protozoa spread

across the next two (2–200 µm); and most metazoans are >0.2 mm (Sieburth, Smetacek &

Lenz, 1978). There can be considerable size differences between larvae, juveniles and adults

in metazoans; so a species may span several size classes.

Classifications based on body size such as macrobenthos, meiobenthos, and nekton,

are for convenience rather than reflecting any true biological classification; so there is no a

priori reason to place a whole species or life stage into a size class. We propose that this trait

is defined as the typical maximum size reached by an individual of the species, be it body

length, or diameter if circular (Table 4). The length of appendages, such as antennae, legs,

wings, or tentacles, is excluded from ‘body length’ although, of course, may be included

in taxon-specific traits. Some taxa may have additional length measurements to body

length, such as wing span of birds, arms of octopuses, tentacles of jellyfish, and antennae

of crustaceans. Thus, ‘body length’ of a coral’s body size will be that of its largest polyp

(not the colony, if colonial), and an octopus’s length would exclude its arms. Where sexes

differ in maximum body-size then the default would be the largest adult body length, but

an additional field could be created where users wish to recognise differences between

sexes. Similarly, traits could be associated with a geographic distribution where they vary

sufficiently between populations. The maximum body weight for a species’ life stage can

be more useful for studies on ecosystem energetics and should also be included where

possible (Table 4). This would include its skeleton and thus its shell unless it was specified

otherwise. The units may be wet weight or dry weight and need to be defined.

Life historyTraits describing the persistence of individuals and/or populations include growth rate and

longevity (life span). Growth rate and age of maturation determine population generation

time. The life span of individuals can indicate population stability over time and dispersal

potential of various life stages (e.g., longer planktonic larva life span) and be measured in

days, months and years. Fecundity indicates potential abundance, population productivity,

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 14/29

and recovery from population decline, and can be measured as the number of eggs per

female per spawning. Recruitment is the actual number of eggs surviving to become

juveniles. However, most of these traits are only available for a few species and some are

difficult to apply at a species level. Other biological traits can characterize the mode of

reproduction of a species, such as whether ovoviviparous, viviparous, hermaphroditic,

parthenogenic, asexual, protogynous, iteroparous or semelparous, involving brooding,

nesting, or parental care. As a first step, we propose to distinguish species with sexual and

asexual reproduction because such information is easily available for most taxa and may

be significant with regard to the ability of a species to disperse, become invasive, and/or

recover from a population decline. As with other traits, a species can be either or both.

PhysiologySpecies responses to climate change, particularly temperature rise and ocean acidification,

will depend on their physiological tolerances. Thermal tolerance may be inferred from

comparing species distributions to environmental data, such as conducted in species

distribution modelling (e.g., Basher, Bowden & Costello, 2014). We do not prioritise the

inclusion of experimental data because they will only be available for a small number

of species. However, we see physiological traits as being of increasing interest and the

availability of data should be reviewed in the future.

EcologicalThe three major classes of traits used in ecology relate to habitat, as covered previously, and

habit and feeding. In ecology, habit is the external appearance or form of a species (Lincoln,

Boxshall & Clark, 1998). Perhaps because more common usage refers to behaviour, this

means a wide variety of traits have been related to habit. Habit is considered important

because it can determine the mode of dispersal and ecological role (e.g., habitat forming)

of species in an ecosystem. Rather than use the term, we propose to focus on the related

trait categories of Mobility and Skeleton (Table 4). Species whose habit forms a physical

habitat for other species are very important in ecology and often define ‘biogenic’

habitats. However, whether species form such habitats can depend on local conditions

and abundance. Species may be colonial, tubicolous, encrusting, produce shells, or erect

(e.g., seaweed) but they do not necessarily form reefs or forests. Future research needs to

consider how to classify such variable attributes of species.

MobilityThe traits influencing a species dispersal potential tend to be encompassed by the growth

form of individual animals (e.g., whether the life stage is mobile or sessile), abundance,

and longevity. Dispersal of individual life stages is a variable of great interest regarding

invasive species. However, it is rarely known from direct measurements and is estimated

from observed colonization events. Thus, we do not propose a classification of dispersal

per se but leave users to select traits that may influence dispersal of their taxa of interest.

Instead, we propose a simple trait of mobility that can be scored as yes or no (if immobile)

(Table 4), or ideally, assigned a distance of ‘ambit’ or dispersal potential (e.g., 0 m, <1 m if

sedentary, >1 m, >10 m, etc.). All pelagic species will be classified as mobile by virtue of

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their medium, but only sessile benthic species as immobile (depending on their life stage).

Where a species may be a host for a parasite or symbionts, then the latter is included in the

trait ‘biological’ under substrata, and parasite under diet (Table 4).

Future development of this trait category may sub-divide it into sessile, sedentary,

mobile (vagile, errant), solitary, aggregated, gregarious, fossorial, and interstitial.

Aggregated could be sub-divided into schooling, swarming, and colonial (fixed together

in colony). Mobile could be sub-divided into swimming, drifting (including rafting),

crawling, burrowing, flying, gliding, and jet propulsion. Variants on these terms can be

significantly different. For example, a species may live in burrows but not create them itself,

so it is ‘burrow living’ but not fossorial.

SkeletonThe presence of hard skeletons, including shells, is an important factor in determining the

fossil record of species. In addition, organisms with calcareous skeletons may be affected by

ocean acidification. Ocean acidification is predicted to increase the physiological costs for

species with calcareous skeletons and shells (Byrne, 2011; Byrne & Przeslawski, 2013), as it

can impact marine organisms through a decreased calcium carbonate (CaCO3) saturation,

thus affecting the calcification rates. The effect of this even increases at high latitudes and

regions that intersect with pronounced hypoxic zones (Fabry et al., 2008), thus stressing

the need to not only know whether a species has calcareous structures, but also to have

information on its geographic distribution.

Many planktonic and benthic groups, such as Coccolithophora, Foraminifera,

Pteropoda, Mollusca, Echinodermata, Crustacea, Cnidaria, Porifera, Bryozoa, Annelida,

Brachiopoda and Tunicata—have CaCO3 skeletal elements. However, it is secreted under

different forms: aragonite, calcite, high magnesium calcite, amorphous CaCO3 or a

mixture of these phases (Mucci, 1983; Lowenstam & Weiner, 1989). Aragonite is about

50% more soluble in seawater than calcite (Mucci, 1983). Documenting the presence of

a hard skeleton in combination with the present CaCO3 phase has been identified as a

priority trait, as this can both be used in determining the fossil record of a species and its

susceptibility to ocean acidification.

Many taxa lack calcareous skeletons. Diatoms have silica based skeletons, so availability

of silica can affect primary productivity. Arthropods and some fungi have chitinous

skeletons, while plants’ cell walls have a range of materials including cellulose and lignin. It

may be important to users whether skeletons occur internally (e.g., fish) and/or externally

to the body wall. Thus, we have prioritised four skeletal materials, calcareous, chitinous,

silicious, and plant cell walls, and whether these form endo- or exo-skeletons (Table 4).

Species without a hard skeleton can be so noted, as well. A considerable number of species

lack such a skeleton, including worm-like taxa, gelatinous zooplankton, sea anemones,

some molluscs (e.g., octopus, slugs). Gelatinous zooplankton, including jellyfish, salps and

ctenophores, tend to be damaged and under-sampled by plankton nets. However, they

are important predators, and some are hazardous to humans and can be considered pests.

Based on the priority traits, a search of WoRMS on ‘pelagic’ and ‘skeleton absent’ will find

soft-bodied plankton of which many could be considered gelatinous.

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Diet and trophic levelFeeding can relate to either what a species feeds on, i.e., its diet if an animal, and/or how

it feeds. Associated traits can become complex and species specific. We thus propose a

simple classification of diet. We exclude scavenger because this is a behaviour rather than

food type. Unless a food source is known it should not be assumed. Often, it is assumed

that small invertebrates are omnivores or detritivores, when the actual importance of

animal, plant and detritus in their diet is unknown, even if feeding has been observed.

Some classifications include decomposers, but decomposition can be by a combination

of carnivores or herbivores and microbial decay. Thus, it is covered by the other feeding

categories and chemoautotrophs (heterotrophs).

We considered traits that described a species feeding method, such as particulate,

suspension, deposit, filter and grazing feeding. These can be important in terms of

classifying the functional role of species in an ecosystem. However, of greater importance is

the trophic level a species occupies; that is, whether it is a detritivore, herbivore, primary,

secondary or tertiary level carnivore. This can be inferred from the species diet and where

available supported by isotope data (e.g., Heymans et al., 2014).

Species’ importance to societyWhat users often wish to know is what the “status” of a species is with regard to its

importance to society. This is not a fundamental trait of the species but reflects its current

‘status’ in some regard. This status may change over time, such as when a new fishery

is established, a species becomes invasive, or it becomes more or less threatened with

extinction. Thus, although the ‘status’ of a species is not a ‘trait’ as such, it is included

in WoRMS. A species conservation status can be indicated by its inclusion in the IUCN

Red List (IUCN, 2014), EU Habitats and Bird Directives (European Union, 1992; European

Union, 2009), OSPAR List of Threatened and Declining Species and Habitats (OSPAR,

2008) and CITES (CITES, 2014) (Tables 5–7). The status of species known to cause

Harmful Alga Blooms (HAB) is recorded within the WoRMS HAB Thematic Database

(Moestrup et al., 2013). Species of importance for fisheries and aquaculture can be

recognised by their listing in official catch statistics (Garibaldi & Busilacchi, 2002).

The IUCN Red List assessments require data on population trends in terms of

abundance, natural mortality rates, and number of breeding individuals. Population–level

are outside the scope of the present paper which concerns species level traits only. However,

future classification could include traits related to fecundity, generation time, age at

maturity, and geographic range, because these are used in the Red List assessments, and

correlated traits such as maximum body size and age. These traits, plus growth rate and

aggregation behaviour, also determine fish species susceptibility to overfishing (Morato,

Cheung & Pitcher, 2006).

A further category that denotes societal importance of a species is its value as an

indicator of ecosystem condition. The Marine Strategy Framework Directive is the key

European marine environmental policy instrument. Its aim is ‘Good Environmental

Status’ in European waters (MSFD 2008/56/EC). Good Environmental Status is divided

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into 11 descriptors, of which five are based on species composition: D1 biological diversity,

D2 non-indigenous species, D3 commercial fish and shellfish, D4 food-webs, and D6

seafloor integrity. Once formalized, these status indicators, and equivalents for other

regions of the world, will be added to the species in WoRMS.

Information on introduced species locations, dates recorded and population trends and

impacts are required for management (Blackburn et al., 2014; Jeschke et al., 2014). This clas-

sification of species is the most difficult of all species attributes because of changing species

status arising from misidentifications, and species becoming invasive in one place, perhaps

temporarily, and not in others. Thus, there is a more complex terminology and structure

required in the database which will be required to be described elsewhere. To date, the

status of almost 1,400 introduced species has been recorded in WoRMS (Pagad et al., 2015).

At present, the conservation of marine species has been focused on chordates, including

mammals, birds, reptiles and fish because these are most threatened with extinction (Ta-

bles 6 and 7). Of European marine species, the EU Bird and Habitats Directives list 100%

of reptiles, 67% of lampreys, 65% of mammals, 61% of birds, 2% of fish, and <0.4% of all

other taxa to be in need of protection (Table 5). Globally, the taxa with most endangered

species are birds (26%), mammals (23%), reptiles (12%), and fish (3%). However, over

2% of cnidarians (hard corals) are considered endangered by IUCN and trade in 20%

is restricted under CITES. Although 74% of marine mammal species are listed under

CITES, only 9% of reptiles, 3% of birds and <1% of fish and other taxa (Table 6). The

same higher taxa dominate species of economic importance as listed by FAO, namely (as

a percentage of WoRMS): 76% mammals, 33% fish, 21% birds, 18% lampreys, and 14%

reptiles. In contrast, introduced species are of very different taxa, namely 5% sipunculans,

3% entoprocts and tunicates, and 2% ctenophores, plants, and annelids (Table 5).

DISCUSSIONBased on the criteria of applicability across most taxa, availability for most species, and

potential usage, we prioritized 10 traits for inclusion in WoRMS (Table 4). Poelen, Simons

& Mungall (2014) similarly prioritised taxonomy, environment, geographic location,

altitude and depth, and functional group (e.g., planktonic) as proposed here. Taxonomy is

already fully implemented, and the others partially. Indeed, as all traits are not available for

all species their completion will be a continuing process. In addition, the conservation and

introduced (potential pest) status of species will need to be regularly reviewed.

We see immediate applications for the traits. Research into species biogeography will

be able to compare the distribution of taxa across ‘environments’ and depth gradients,

and classify them by body size and trophic levels. OBIS uses WoRMS as their taxonomic

standard and could also use the traits. Then OBIS users could select species not just by

taxonomy but by their traits and, for example, conservation status or fishery importance.

Ocean acidification studies will be able to compare the distribution of taxa with different

skeletal composition. Paleontologists will be able to compare the species richness of taxa

likely to be better preserved as fossils with taxa without durable skeletons. Gelatinous

zooplankton occur in different phyla but could now be grouped by this trait. Analyses

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 18/29

Table 5 Numbers of species in ERMS and WoRMS, and that are alien, cause HAB, and of conservation and economic importance. The numberof species in higher taxa that occur in the European and World Registers of Marine Species (ERMS, WoRMS); are considered alien (=introduced)

(or their origin in uncertain or unknown); been listed as of conservation importance by the European Union Birds or Habitats Directives; listed ofregional ecological importance under the Oslo-Paris Convention (OSPAR); are associated with Harmful Algal Blooms (HAB); or are listed as beingof international commercial fishery or aquaculture importance by the Food and Agricultural Organisation (FAO).

Taxon kingdom,phylum, or class

ERMS WoRMS Alien Originunknown

Originuncertain

EU directive OSPAR HAB FAO

Agnatha 6 93 0 0 0 3 0 0 17

Annelida 2,170 12,658 158 21 19 0 0 0 19

Aves 234 645 2 0 0 91 9 0 133

Bacteria 181 1,716 4 0 0 0 0 1 1

Bryozoa 800 6,112 58 4 3 0 0 0 0

Chaetognatha 41 131 1 0 0 0 0 0 0

Chelicerata 517 2,939 4 0 1 0 0 0 12

Chromista 3,929 20,285 172 26 1 0 0 115 42

Cnidaria 1,294 10,760 76 6 6 1 0 0 86

Crustacea 7,062 53,321 287 15 6 1 1 0 643

Ctenophora 39 187 4 0 0 0 0 0 1

Echinodermata 652 7,277 15 1 1 1 0 0 151

Echiura 37 197 1 0 1 0 0 0 0

Entoprocta 60 174 4 1 0 0 0 0 0

Fungi 399 1,363 8 0 0 0 0 0 0

Hexapoda 88 1,461 2 0 0 0 0 0 0

Mammalia 54 140 1 0 1 35 4 0 107

Mollusca 4,294 45,128 291 9 8 4 4 0 1,323

Nematoda 2,103 7,012 1 0 0 0 0 0 0

Pisces 1,451 17,858 206 3 6 28 22 0 5,892

Plantae 1,666 8,800 157 16 3 3 0 0 154

Platyhelminthes 2,133 12,134 16 2 3 0 0 0 0

Porifera 1,542 8,383 11 1 4 0 0 0 20

Reptilia 5 107 1 0 0 5 2 0 15

Rotifera 109 186 2 0 0 0 0 0 2

Sipuncula 42 147 7 0 0 0 0 0 2

Tunicata 495 3,031 59 20 1 0 0 0 24

TOTAL 33,149 227,585 1,548 125 64 172 42 116 8,644

could test whether threatened, introduced and/or invasive species are a random subset of

all marine species, or have particular traits that may predispose them to being threatened,

introduced or becoming invasive respectively. For example, are mobile and/or asexual

species more likely to be introduced, and less likely to be of conservation concern, because

only one individual is required for dispersal?

Some users may be most interested in secondary traits, that is, traits dependent on

combinations of the primary traits reviewed here. For example, bioturbation potential is

predicted from a combination of known information for related species with regard to

mobility, burrowing behaviour, biomass and abundance (Queiros et al., 2013). Dispersal

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Table 6 Number of species assessed for conservation concern. The number of species in higher taxa that had their conservation risk assessed on theglobal IUCN Red List as Extinct, Extinct in the wild, Critically Endangered, Vulnerable, Near threatened; or Least concern; and international traderestricted (listed by CITES). Taxa not represented in these categories were: Acanthocephala, Agnatha, Amphibia, Annelida, Brachiopoda, Bryozoa,Cephalochordata, Cephalorhyncha, Chaetognatha, Chelicerata, Ctenophora, Cycliophora, Dicyemida, Echiura, Entoprocta, Fungi, Gastrotricha,Gnathostomulida, Hemichordata, Hexapoda, Myriapoda, Myxozoa, Nematoda, Nemertea, Orthonectida, Phoronida, Placozoa, Platyhelminthes,Protozoa, Rotifera, Sipuncula, Tardigrada, Tunicata, Viruses, Xenacoelomorpha.

Taxon kingdomor phylum

Extinct Extinctin wild

Criticallyendangered

Endangered Vulnerable Near threatened Least concern CITES

Chromista 0 0 4 1 1 0 0 0

Plantae 1 0 8 6 16 12 108 6

Porifera 0 0 0 0 0 0 0 0

Cnidaria 0 0 7 25 204 176 297 2,097

Mollusca 4 0 7 16 36 30 769 2

Crustacea 0 0 6 1 1 2 162 0

Echinodermata 0 0 0 0 9 1 111 1

Pisces 1 0 60 93 314 236 3,469 95

Reptilia 0 0 4 3 6 4 48 9

Aves 9 0 26 58 86 78 600 22

Mammalia 4 0 3 12 17 9 44 104

TOTAL 19 0 126 215 691 548 5,608 2,336

Table 7 Number of species in taxa not included in Tables 5 and 6. Number of species in taxa in theEuropean and World Registers of Marine Species (ERMS, WoRMS) but not represented in any of thecategories in Tables 5 and 6.

Taxon kingdom or phylum ERMS WoRMS

Acanthocephala 62 446

Amphibia 0 1

Archaea – 119

Brachiopoda 39 395

Cephalochordata 2 30

Cephalorhyncha 62 236

Cycliophora 1 2

Dicyemida 17 122

Gastrotricha 256 491

Gnathostomulida 25 98

Hemichordata 17 130

Myriapoda 13 68

Myxozoa 212 473

Nemertea 378 1,359

Orthonectida 19 25

Phoronida 9 17

Placozoa 1 1

Protozoa 350 623

Tardigrada 83 170

Viruses – 111

Xenacoelomorpha 200 423

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 20/29

potential may be predicted by combinations of mobility and environment (Angert et al.,

2011). We understand some users will want additional sub-divisions of traits, for example,

of salinity by estuarine ecologists (Reusser & Lee, 2011). The latter authors also sub-divided

benthic, pelagic, and reproductive traits, but then combined environment, habitat, and

seascapes, within a very broad definition of biogeography. Users that wish to implement

specialist traits for a particular taxon are welcome to do so, and WoRMS is available

to provide the infrastructure. If these are unique to the taxon then the development

of such trait classifications is simplified. However, where they may overlap will require

consideration by specialists on other taxa.

It is relatively easy to add more trait fields to a database. However, this can increase

complexity, redundancy, duplication, and overlap between traits. We thus recommend that

expansion of the trait classification in databases proceed cautiously and concisely, only

adding traits with a proposed use and that are available for the taxa of interest.

ACKNOWLEDGEMENTSWe thank the following for helpful discussion at workshops and by correspondence:

Adrian Glover, Madeleine Brasier, Geoff Boxshall (Natural History Museum, London);

Andreas Kroh (Natural History Museum Vienna, NHM-WIEN); Anna Tornroos (ABO);

David Johns and Abigail McQuatters-Gollop (SAHFOS); Jan Vanaverbeke and Olivier

de Clerck (UGent.); Jen Hammock (EoL); Pelin Yilmaz (MPI-Bremen); Stephane Pesant

(MARUM); Tammy Horton (NOC); Tom Webb (Sheffield University), Stefan Garthe

(Christian-Albrechts-University Kiel); Eva Chatzinikolaou, Christos Arvanitidis, Frederica

Camisa, Thanos Dailianis, Sarah Faulwetter, Evangelos Pafilis, Christina Pavloudi,

Aikaterini Vasileiasou (HCMR, Hellenic Centre for Marine Research); Eric Stienen (INBO,

Instituut voor Natuur- en Bosonderzoek); Mark Tasker and Eunice Pinn (JNCC, Joint

Nature Conservation Committee); Olivia Langmead (Marine Biological Association,

Plymouth); Peter Herman (NIOZ); Sofie Vranken, Aina Trias Verbeeck, Daphnis De

Pooter, Wim Decock, Bart Vanhoorne, Francisco Hernandez, Klaas Deneudt (VLIZ),

Regarding introduced species we especially thank Shyama Pagad, Piero Genovesi (IUCN

Invasive Species Specialist Group), Stelios Katsanevakis and Ana Luisa Nunes (EASIN).

The WoRMS fossils classification was developed by Serge Gofas (University of Malaga),

Bruce Hayward (Geomarine, New Zealand), Simon Schneider (CASP), and Andreas Kroh

and Thomas A. Neubauer (NHM-WIEN). We thank Astrid Schmidt-Kloiber, Anne-Marie

Power, Magnus Johnson and an anonymous referee for helpful comments that improved

the paper.

ADDITIONAL INFORMATION AND DECLARATIONS

FundingThis paper was supported by the European Marine Observation Data Network (EMOD-

net) Biology project (www.emodnet-biology.eu), funded by the European Commission’s

Directorate—General for Maritime Affairs and Fisheries (DG MARE). The funders had no

Costello et al. (2015), PeerJ, DOI 10.7717/peerj.1201 21/29

role in study design, data collection and analysis, decision to publish, or preparation of the

manuscript.

Grant DisclosuresThe following grant information was disclosed by the authors:

European Commission’s Directorate—General for Maritime Affairs and Fisheries (DG

MARE).

Competing InterestsSimon Claus, Stefanie Dekeyzer, and Leen Vandepitte are employees of Flanders Marine

Institute (VLIZ); Dan Lear and Harvey Tyler-Walters are employees of Marine Biological

Association; and Eamonn O Tuama is an employee of Global Biodiversity Information

Facility.

Author Contributions• Mark John Costello conceived and designed the experiments, performed the experi-

ments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper,

prepared figures and/or tables, reviewed drafts of the paper.

• Simon Claus, Stefanie Dekeyzer and Eamonn O Tuama conceived and designed the

experiments, performed the experiments, contributed reagents/materials/analysis tools,

wrote the paper, reviewed drafts of the paper.

• Leen Vandepitte, Dan Lear and Harvey Tyler-Walters conceived and designed the

experiments, performed the experiments, contributed reagents/materials/analysis tools,

wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Data AvailabilityThe following information was supplied regarding the deposition of related data:

All data is publicly available in the World Register of Marine Species: http://www.

marinespecies.org.

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